Control system for a wind power plant

ABSTRACT

Control system for a wind power plant A control system for a wind power plant comprises sensor means for the detection of measurement values to be used for direct or indirect quantification of the current loading and/or stress of the turbine occurring in dependence on the local and meteorological conditions. Downstream of said detection means, an electronic signal processing system is provided, operative to the effect that the power reduction required in the optimized condition of the wind power plant will be restricted to obtain optimum economical efficiency under the current operating conditions, both in cases of winds in the range of the nominal wind velocity and in cases of high wind velocities.

BACKGROUND OF THE INVENTION

[0001] The annual energy output to be obtained by a wind turbinedecisively depends, apart from the performance of the generator asinstalled, on the rotor diameter. Thus, for increasing the efficiency,it is desirable to use rotors of the largest possible size. However,when enlarging the rotor diameter while otherwise operating the plantunder the same conditions, difficulties arise because the stressesacting on the rotor, the nacelle, the tower and the foundation willincrease at least by the second power of diameter. Presently usualratios between the performance of the generator as installed and therotor area (rating) are in a range from 460 to 330 W/m², the lattervalue pertaining to pitch-regulated turbines optimized for inland use.

[0002] According to an approach frequently used in wind energytechnology, an existing turbine to be used in sites with weak winds canbe retrofitted to have a larger rotor diameter, with the switch-offspeed being lowered from e.g. 25 m/s to 20 m/s to safeguard that thestresses will remain in the allowable range.

[0003] Further, in plants with blade adjustment (pitch-type plants), itis a usual practice to adjust the rotor blades towards the direction ofthe feathered pitch already before the rated power is reached, thusreducing the stresses (particularly those acting on the tower).

[0004] According to a more complex and longer-known approach forreducing the above mentioned stresses, the rotational speed of therotors and/or the power output of the turbine can be decreased in caseof high wind velocities. For technical reasons (design of thetransmission and/or generator and/or converter), decreasing therotational speed of the rotors will have the effect that the poweroutput is reduced at least according to the same ratio. Since, however—as widely known (cf. for instance “The Statistical Variation of WindTurbine Fatigue Loads”, Riso National Laboratory, Roskilde DK, 1998)—thelargest part of the high stresses that tend to shorten the lifespan willoccur at high wind velocities, the above approach is successfully usedparticularly at inland locations for improving the efficiency of windenergy plants. Particularly at inland locations, use can thus be made oflarger rotors which during the frequent low wind velocities will yieldhigher energy outputs but upon relatively rare high wind velocities willhave to be adjusted correspondingly.

[0005] Further, the state of the art (DE 31 50 824 A1) includes anopposite approach for use in a wind turbine with fixed rotational speed,wherein, during high wind velocities with merely low turbulences, thepower output of the turbine can supposedly be increased beyond the ratedpower by adjusting the rotor blade angle through evaluation of signalsfrom a wind detector.

SUMMARY OF THE INVENTION

[0006] The above outlined known approach of reducing the power output incase of high wind velocities makes it possible—e.g. in a variable-speedpitch plant with a control algorithm for controlling the rotor speed onthe basis of the pitch angle averaged over time—to obtain very highratios between the rotor diameter and the generator performance withoutan accompanying increase of component fatigue as compared toconventionally designed turbines. A rating of 330 to 280 W/m² can beobtained and is economically reasonable especially at inland locations.

[0007] For reasons of safety, the design of the towers of wind powerplants is on principle determined on the basis of very unfavorableassumptions (e.g. high wind turbulences and maximum wind distribution inthe designed wind zone); therefore, in the majority of locations,considerable safety margins of the power output are left unused in theturbines. Thus, the problem exists how these normally existing safetymargins can be utilized for improving the efficiency of the turbine.

[0008] According to the instant invention, this object is fulfilled byperforming, by means of an already existing or additionally installedsensor arrangement with connected signal processing system in the windpower plant, a direct or indirect quantification of the current turbinestresses. By comparison with allowable stresses (or correlating values)detected by computation or empirically, the turbine will always beoperated with a rotor speed and a power yield which are optimized underthe economical aspect.

[0009] Other than in the normally used state of the art wherein theoperational control process is provided to control the blade angleand/or the rotational speed according to fixed functions in dependenceon power, blade angle or wind velocity, this novel control process is tobe performed only to the extent required due to the local conditions ormeteorological conditions at the respective point of time to thus obtainoptimum efficiency.

[0010] A simple algorithm suited for the above purpose is based on thestatistical evaluation of one, a plurality or all of the measurementvalues (e.g. rotor speed, generator performance, pitch angle, pitchrate, wind velocity and wind direction) mentioned among those operatingdata which are anyway continuously detected in many present-day windpower plants (e.g. variable-speed pitch plants).

[0011] In the present context, the term “statistical evaluation” ismeant to include at least the continuous detection of the minimum,maximum and average values and the standard deviation for a plurality ofsliding time intervals Δt (30 s to 60 min.). More-complex statisticalevaluations of the operating data or the derivations thereof will resultin a more successful control. Since wind is a stochastically distributedvalue, a reasonable detection and arithmetical representation of themeasurement values can be performed only by means of distribution andprobability functions or spectra. On the basis of measurements orsimulation computations, the correlation coefficients of the statisticaldata relative to the local and meteorological conditions and the currentstresses on the components can be determined with sufficient accuracy.For instance, the average pitch angle and the average rotor speed for agiven turbine configuration are in direct relation to the average windvelocity; the standard deviation of the two former values allows for aconclusion on the turbulence intensity (gustiness) of the wind. Thus,besides the directly measured operating data, also important stress data(e.g. the blade bending moment and the thrust acting on the tower) canbe statistically evaluated, These actual distributions of the stressesor of the values directly related thereto are compared to desireddistribution functions which have been obtained by computation orempirically. These desired functions can be detected for each locationas suited for the specific application and be stored in a data memory ofthe control system.

[0012] An example of a preferred embodiment of the control system usingthe inventive control strategy will be explained in greater detailhereunder in connection with the accompanying drawing.

BRIEF DESCRIPTION OF THE DRAWING

[0013] The sole drawing is a block diagram of the control system usingthe control strategy according to the instant invention.

DESCRIPTION OF A PREFERRED EMBODIMENT

[0014] In the block diagram, angular boxes are meant to represent signalprocessing systems or computing modules of a larger software packageinstalled in a signal processing system. Laterally rounded boxesrepresent input data for the control system, irrespective of whetherthese data are measured on the turbine or supplied from an externalsource. Boxes curved on top and bottom represent data stores containingall data which are required for the execution of the control algorithmand are made available through the internal data detection or analysis,or are supplied from external data sources. Elements represented insolid lines are absolutely required for the control system; elementsrepresented in dotted lines are optional components which improve thefunction of the control system and thus allow for a higher energy yieldeven though they will cause an increasing complexity of the controlconcept.

[0015] Schematically shown to the left of the vertical dash-dotted linein the left half of the drawing is a schematic representation of thecontrol systems used according to the state of the art. The input valuesare the operating values provided to be permanently detected by themeasurement sensors, such as the rotor and generator speeds n_(R) andn_(G), respectively, the electrical power P_(el), the generator torqueM_(G), the blade or pitch angle θ and the pitch rate θ′, and the windvelocity v_(w) and the wind direction v_(dir). On the basis of thesemeasurement values, the turbine is controlled according to an algorithmimplemented in the main computer for operating the plant (standardcontrol). The regulated quantities are the pitch angle θ and/or thegenerator moment M_(Gsoll) (e.g. also by selection of the generatorstage in asynchronous turbines with switchable polarity). The controlloop wherein, by means of the actuators, the desired values are turnedinto actual values which then will be detected as operational values tobe used as control input values as schematically indicated, has beenomitted from the block diagram for better survey.

[0016] According to the state of the art, additional measurement values(e.g. temperatures, hydraulic pressures, tower head accelerations, oillevel and wear indications) allow for the detection of certainconditions of the plant and, if required, will result in shut-down ofthe turbine.

[0017] In the inventive control system, the operating data are subjectedto a statistical data pick-up and are stored as spectra or distributionsin a data store. Optionally, In the so-called loading model, thestatistical operating data are converted into statistical stress data bymeans of the correlation functions obtained in the simulationcomputations.

[0018] More-complex algorithms are based on additional measurementvalues which are more closely related to the stresses, and suchalgorithms allow for a distinctly more precise detection of the existingdistribution of stresses and thus for a closer approach to the limitingvalues dictated by the respective design, thus obviating the need forthe safety margins necessitated in simple algorithms.

[0019] The sensors on the turbine can be provided, inter alla, asacceleration sensors on the tower head and the rotor blades, and/or wirestrain gauges on representative points of the support structure (e.g. onthe blade roots, rotor shaft, base of the tower).

[0020] By inclusion of additional wind-field data which in the idealcase characterize the undisturbed on flow before the rotor, the controlbehavior can be considerably improved. Generally, for this purpose, usecan be made of laser-optical and/or acoustic (ultrasonic) measuringmethods which are suited both for measurements on individual points inthe wind field and for measurements of complete wind profiles or windfields in the rotor plane or also far before the rotor plane. A furtherimprovement of the control behavior is accomplished by linking thecontrol systems of the different turbines of a wind park to each other;the considerably enlarged data base obtained in this manner willsafeguard a faster but still statistically reliable response of thecontrol systems.

[0021] All of the detected spectra or distributions will be stored,preferably classified according to operating year, average wind velocityand turbulence intensity.

[0022] Upon sufficiently accurate determination of the stresses throughdetection of stress data, it appears reasonable to transform the stresschanges into so-called Markov matrices by use of known counting methodsor on the basis of the average values (online rainflow counting). Tothis end, microchips which have already entered the stage of industrialproduction are available from the field of aviation and spacetechnology.

[0023] The distributions which have been measured or have been computedfrom the measurement data are compared to the desired distributions ofthe same values. For this purpose, data on design, planning andfinancing are externally collected, input into the system and stored ina data store. Using an economy model, the desired distributions arederived from these data. Design data include e.g. the allowable loadingdistributions for the individual components; an example of the planningdata is the expected wind distribution at the location; and thefinancing data include, in addition to the overall project costs, thecurrent credit costs, the energy profits required according to thefinancing plan, and the current charges for power supply. Monthlyupdates of these data per remote monitoring can be used for immediateadaptation of the control system to changes of the basic conditions,e.g. to changes of the charges for power supply or of the financingcosts, new recognitions on the allowable stresses on the components, oreven improved control algorithms. Data on the supraregional annual winddistribution make it possible, on the one hand, by comparison with themeasured wind distribution at the location, to perform a correction ofthe planning data; on the other hand, in less favorable wind years, theturbine can be operated by use of a “sharper” power characteristic curvefor keeping up with the requirements of the financing plan.

[0024] In the operating level control unit, the thus obtained desireddistributions are compared with the actual distributions. This way, theoptimum operating level under the current meteorological and localconditions is computed. The regulated quantities θ_(opt) (blade angle)and M_(Gopt) and n_(Gopt) (generator moment and generator speed,respectively) are to be understood as preset average values while, onthe other hand, the current desired values supplied by the standardcontrol system for adjustment to wind turbulences may temporarilydeviate from these average values,

[0025] With the availability of such a control system, it may beadvisable to operate the turbine with higher power yield in the firstyears of operation in order to lower the financing costs as quickly aspossible, whereas, in later years, a low-stress operation with reducedenergy yield and a resultant lengthened lifespan may be consideredoptimum under the economic aspect.

[0026] In the ideal case, the above described control system is improvedby the feature of an on-line detection of the current energy generatingcosts (Cost Of Energy COE). For this purpose, it is required that theloading model is combined, downstream thereof, with a stress model forthe individual components of the plant (a restriction to the maincomponents, i.e. the rotor blades, the transmission, the generator, theconverter and the tower will be sufficiently accurate), and with adamage model. The stress model transforms the loading distributions intostress distributions on representative points of the components and isbased on the methods applied in the design of the components. Theresults from finite element calculations can be summarized e.g. byconsideration of merely a small number of compliance factors for somecritical points. The damage model compares the existing loadinginfluences (e.g. Woehier lines) and thus computes the current componentdamage. (The damage of a component permits conclusions on the remaininglifespan). Therefore, the damage model has to rely on a data base of thematerial or component behavior which is made available from an externalsource and should be of a modular type so as to be adaptable to the mostup-to-date recognitions (e.g. Woehler tests on original components,practical experiences from the serial production) in the course of thelifespan of the turbine. Since, in the present state of the art,particularly the material behavior has to be estimated on a veryconservative basis due to lack of a sufficient data basis, the aboveadaptation feature offers a wide potential for yield increase.

[0027] If the damage model has been suitably refined to allow for anonline calculation of the damage and thus also of the damage rate forthe important main components, the results of such calculation can beeasily used for determining an equivalent damage rate for the wholeturbine (Equivalent Damage Rate, EDR). The equivalent damage rate (unit:US$/h) is a measure for the costs per time unit incurred by damage inthe current operating condition of the turbine. The current energygenerating costs can then be obtained by dividing the sum of the EDR andthe other operating costs by the current power fed into the grid.

[0028] On this ideally refined level of the control strategy wherein theeconomical efficiency of the wind turbine is reduced to the decisivecharacteristlc factor “cost of energy COE”, the efficiency model has tobe adapted to determine, as a value for comparison to the current COE,the maximum allowable COE where the turbine is still allowed to beoperated. Should the current COE values be too high in situations withweak winds, the turbine will be taken off the grid. Should the currentCOE values be too high in situations with high wind velocities, theoperating level control unit will lower the excessive stresses bysuitably controlling the turbine, thus decreasing the COE value. Thus,by the above online COE determination, the optimum operating level withthe lowest possible COE values can be obtained for the current local andmeteorological conditions by use of a simple control loop. On thisoptimum operating level, if the COE values are higher than the maximumallowable COE value determined by the efficiency model, the turbine willbe brought to a standstill until more-favorable conditions occur (e.g.lower turbulences or lower wind velocity). Thus, during low turbulences,the turbines can supply power still in case of much higher windvelocities than had been possible in the state of the art.

[0029] As a further possible component, schematically illustrated in theright-hand edge region of the drawing to the right of the verticaldash-dotted line, a short-time control unit may be provided forreduction of temporary loading peaks. The input data of said unitinclude loading data and optionally also wind field data, which—otherthan in the operating level control unit—are not evaluated statisticallybut subjected to a current value analysis; in a signal processing modelalso referred to as a loading prognosis, predictions can thus be made onloading peaks which will be reduced by the short-time control unitthrough limitation the pitch angle or the rotor speed.

[0030] Therefore, particularly when using of data of neighboring windpower plants located upstream relative to the wind direction, theloading of the plant and thus also the current COE value during windvelocities above the nominal wind are massively reduced; notably,turbines located behind other turbines in the wind direction can reactexactly and with a suitable delay on wind occurrences which have beenregistered in the turbine arranged upstream. Thus, the unavoidabledisadvantages (trailing turbulences) for the following turbines can becompensated for.

[0031] For guaranteeing that the available potential of the plant willnot be reduced in case of a possible failure of one component of theabove control system, the operating control system should preferably bedesigned such that the standard control system illustrated on the leftside of the drawing is separated, under the hardware aspect, from theother components of the operating level control unit. Thus, should theoperating level control unit be not available, the turbine willnonetheless remain connected to the grid, even though it will then besubjected to the power limitation for high wind velocities as providedby the state of the art.

[0032] The described control strategy is by no means limited to theillustrated preferred embodiment for a variable-speed pitch plant but isin its essence also useful for pitch plants designed for fixed speeds orpole reversal, or for stall or active stall plants.

[0033] Further, a large number of specific details and refinements ofthe system can be contemplated (additional measurement values, damagemodules for further components of the plant etc.), all of them followingthe basic idea of determining the optimum operating time under thecurrent local and meteorological conditions.

1. A control system for a wind power plant, comprising: sensor means forsensing measurement values to be used for direct or indirectquantification of the current loading or stress, or both, of the turbineoccurring depending on the local and meteorological conditions, anddownstream of said sensor means, an electronic signal processing systemoperative to the effect that the power reduction required in theoptimized condition of the wind power plant will be restricted to obtainoptimum economical efficiency under the current operating conditions,both in cases of wind in the range of the nominal wind velocity and incases of high wind velocities.
 2. The control system according to claim1 wherein the wind power plant is designed for blade adjustment in thedirection of the feathered pitch (pitch-type plant).
 3. The controlsystem according to claim 1 wherein the wind power plant is a stall oractive stall plant.
 4. The control system according to claim 1 whereinthe wind power plant is designed for variable-speed operation or for atleast two fixed operating speeds.
 5. The control system according toclaim 1 wherein the measurement values monitored by said sensor meansinclude one or a plurality of the values of the operating data from thegroup including the rotor speed, the generator speed, the electricpower, the generator rotational moment, the blade angle, the blade angleadjustment rate, the wind velocity and the wind direction.
 6. Thecontrol system according to claim 1 wherein the measurement valuesmonitored by said sensor means include accelerations in the rotor bladesand/or the nacelle and/or the tower.
 7. The control system according toclaim 1 wherein the measurement values monitored by said sensor meansinclude stretching on representative points of the components (e.g. theblade roots, rotor shaft, the nacelle base, the base of the tower) ordeformations in elastic bearings.
 8. The control system according toclaim 1 wherein the measurement values monitored by said sensor meansinclude data of the wind field in or before the rotor plane.
 9. Thecontrol system according to claim 1 wherein the measurement valuesmonitored by said sensor means include measurement data from other windpower plants supplied via a network.
 10. The control system according toclaim 1 wherein, using a signal processing system, the measurementvalues monitored by said sensor means are processed into actual spectra(online rainflow counting) or actual distribution functions.
 11. Thecontrol system according to claim 1 wherein, using a signal processingsystem, damages of the components are computed from the actual spectra.12. The control system according to claim 1 wherein, using a signalprocessing system, desired spectra or desired distribution functions arecomputed from externally supplied data on the economy of the turbine.13. The control system according to claim 1 wherein, using a signalprocessing system, current energy generating costs (online Cost OfEnergy COE) are computed from the evaluated externally supplied data.